A Hydrologic Forecast Method Based on LSTM-BP

Hydrological data is sequential and non-linear,with high uncertainty and complexity. The results of hydrological forecasting using a single model are often dissatisfactory. Therefore,this paper puts forword a multi-model combination forecast model,based on LSTM and BP neural network,to forecast the flood. The model takes hydrological data records of the past year obtained from the Ziwuhe River as an example,the test results show that the effects of multi-model combination forecast model are better than that of a single model,and the stability and accuracy of forecasting are also improved,which provides a new idea for hydrological forecasting.